Sjogren's syndrome (SS) is a chronic, debilitating, potentially life-threatening autoimmune disorder that causes irreversible damage to the lacrimal and salivary glands resulting in a loss of tear and saliva production, severely impairing quality of life. SS affects an estimated 2 to 4 million Americans, with as many as 50% of individuals with SS remaining undiagnosed and delays of diagnosis of up to 7 years from the initial onset of symptoms. Early diagnosis of SS is critical to enable early treatment and surveillance for serious complications such as lymphoma. Dry eye disease, or keratoconjunctivitis sicca (KCS), is highly prevalent in the general population and is one of the key features of SS, preceding the systemic findings of SS by an average of 10 years. Approximately 11% of dry eye patients presenting to an eye care professional have underlying SS. However, because the diagnostic work-up for SS involves collaboration among multiple specialists, is time-consuming and expensive, it is not feasible to work-up all KCS patients for SS. Because SS patients often first seek care for dry eye, ophthalmologists have a unique opportunity to screen patients for SS but are severely hampered by a lack of evidence-based, accurate screening tools. The objective of this proposal is to develop and validate a new clinical prediction model for detecting SS, and to increase our understanding of the important relationship between KCS and SS. We propose to leverage clinical data and biospecimens from the National Institute of Health (NIH)-sponsored Sjogren's International Clinical Collaborative Alliance (SICCA) study, in order to gain deeper insight into the characteristics of different subgroups of KCS patients with or without SS. Our overall hypothesis is that the SICCA data and biospecimens can be used to develop an effective screening tool for dry eye patients to distinguish patients with KCS-only from those with SS. Moreover, we hypothesize that the assessment of novel serum antibodies [SP-1 (salivary gland protein-1), CA-6 (carbonic anhydrase-6), and PSP (parotid secretory protein)] will improve the accuracy of the tool (9). We will evaluate these hypotheses with 3 specific aims: Aim 1: Determine if novel candidate SS antibody status distinguishes KCS subjects without SS from those with SS, and predicts conversion of KCS patients to SS; Aim 2: Develop a clinical prediction model using symptoms (extra-ocular and ocular), ocular signs, and novel antibody status for distinguishing KCS patients without SS from those with SS; Aim 3: Validate the clinical prediction model in a new cohort of KCS patients. We anticipate that our new screening tool will shift the current clinical paradigm by allowing ophthalmologists to efficiently identify and refer dry eye patients with a high likelihood of having SS. We will also establish a new dry eye cohort and biospecimen bank for future studies. Our overall goal is to reduce the long delays in the diagnosis of SS that lead to delayed treatment and inadequate surveillance for serious complications.